A Simple Wavelet Transform with Fine Time and Frequency Sampling

Wavelet transform performs frequency transform with different time window widths to enable accurate time-frequency analysis for sensing. Time and frequency sampling of scalogram are not uniform to eliminate redundancy. One method achieves fine time sampling with fewer operations, but the frequency direction sampling is not uniform or fine, and sidelobes are high. To address these problems, this study proposes a simple wavelet transform with fine time and frequency sampling. The proposed method consists of phase multiplication and signal addition. Frequency transform of any time window width is possible by changing the additive width of the signal. Furthermore, by adding the results, wavelet transform using a triangular window that lowers sidelobes is realized using a small number of complex multiplication operations. When the proposed method is applied to a chirp waveform, the frequency transition of the signal could be finely confirmed.

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Publication Details

Journal
IEICE Communications Express
Published
2024-08-09
DOI
https://doi.org/10.23919/comex.2024xbl0117
Citations
1
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
0.25
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article

A Simple Wavelet Transform with Fine Time and Frequency Sampling

Tomoya Yamaoka, Tadashi Oshima
1 citations
IEICE Communications Express
Image and Signal Denoising Methods
0.25
article

A Simple Wavelet Transform with Fine Time and Frequency Sampling

Tomoya Yamaoka, Tadashi Oshima
article en
1 citations

Abstract

Wavelet transform performs frequency transform with different time window widths to enable accurate time-frequency analysis for sensing. Time and frequency sampling of scalogram are not uniform to eliminate redundancy. One method achieves fine time sampling with fewer operations, but the frequency direction sampling is not uniform or fine, and sidelobes are high. To address these problems, this study proposes a simple wavelet transform with fine time and frequency sampling. The proposed method consists of phase multiplication and signal addition. Frequency transform of any time window width is possible by changing the additive width of the signal. Furthermore, by adding the results, wavelet transform using a triangular window that lowers sidelobes is realized using a small number of complex multiplication operations. When the proposed method is applied to a chirp waveform, the frequency transition of the signal could be finely confirmed.

IEICE Communications ExpressVol. 13(10)
Mitsubishi Electric (Japan) (JP)
Openalex Percentile: Top 49%
Image and Signal Denoising Methods
0.25
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A Simple Wavelet Transform with Fine Time and Frequency Sampling — Tomoya Yamaoka, Tadashi Oshima · IEICE Communications Express (2024) | TGRS Research Map | TGRS